Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to growing awareness of their influence on a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications involving microorganisms, both in vivo and in silico, have been developed in the context of isolated microbes. In vivo microbial consortia development is extremely difficult and costly because it implies replicating suitable environments in the wet-lab. Computational approaches are thus a good, cost-effective alternative to study microbial communities, mainly via descriptive modelling, but also via engineering modelling. In this review we provide a detailed compilation of examples of engineered microbial communities and a comprehensive, historical revision of available computational metabolic modelling methods to better understand, and rationally engineer wild and synthetic microbial communities.Microorganisms rely on protein interactions to transmit signals, react to stimuli, and grow. One of the best ways to understand these protein interactions is through structural characterization. However, in the past, structural knowledge was limited to stable, high-affinity complexes that could be crystallized. Recent developments in structural biology have revolutionized how protein interactions are characterized. The combination of multiple techniques, known as integrative structural biology, has provided insight into how large protein complexes interact in their native environment. In this mini-review, we describe the past, present, and potential future of integrative structural biology as a tool for characterizing protein interactions in their cellular context.Recent advances in enzymatic electrosynthesis of desired chemicals in biological-inorganic hybrid systems has generated interest because it can use renewable energy inputs and employs highly specific catalysts that are active at ambient conditions. However, the development of such innovative processes is currently limited by a deficient understanding of the molecular mechanisms involved in electrode-based electron transfer and biocatalysis. Mechanistic studies of non-electrosynthetic electron transferring proteins have provided a fundamental understanding of the processes that take place during enzymatic electrosynthesis. Thus, they may help explain how redox proteins stringently control the reduction potential of the transferred electron and efficiently transfer it to a specific electron acceptor. The redox sites at which electron donor oxidation and electron acceptor reduction take place are typically located in distant regions of the redox protein complex and are electrically connected by an array of closely spaced cofactors. These groups function as electron relay centers and are shielded from the surrounding environment by the electrically insulating apoporotein. In this matrix, electrons travel via electron tunneling, i.e. hopping between neighboring cofactors, over impressive distances of upto several nanometers and, as in the case of the Shewanella oneidensis Mtr electron conduit, traverse the bacterial cell wall to extracellular electron acceptors such as solid ferrihydrite. Here, the biochemical strategies of protein-based electron transfer are presented in order to provide a basis for future studies on the basis of which a more comprehensive understanding of the structural biology of enzymatic electrosynthesis may be attained.Melanized fungi have been isolated from some of the harshest radioactive environments, and their ability to thrive in these locations is in part due to the pigment melanin. Melanin imparts a selective advantage to fungi by providing a physical shield, a chemical shield, and possibly a signaling mechanism. https://www.selleckchem.com/ In previous work we demonstrated that protracted exposure of the melanized yeast Exophiala dermatitidis to mixed alpha-, beta-, and gamma-emitting radiation resulted in an adapted strain able to mount a unique response to ionizing radiation in the environment in a melanin-dependent fashion. By exploring the genome and transcriptome of this adapted melanized strain relative to a non-irradiated control we determined the altered response was transcriptomic in nature, as whole genome sequencing revealed limited variation. Transcriptomic analysis indicated that of the adapted isolates analyzed, two lineages existed one like the naïve, non-adapted strain, and one with a unique transcriptomic signature that exhibited downregulation of metabolic processes, and upregulation of translation-associated genes. Analysis of differential gene expression in the adapted strain showed an overlap in response between the control conditions and reactive oxygen species conditions, whereas exposure to an alpha particle source resulted in a robust downregulation of metabolic processes and upregulation of DNA replication and repair genes, and RNA metabolic processes. This suggest previous exposure to radiation primes the fungus to respond to subsequent exposures in a unique way. By exploring this unique response, we have expanded our knowledge of how melanized fungi interact with and respond to ionizing radiation in their environment.Alternative splicing contributes to the majority of protein diversity in higher eukaryotes by allowing one gene to generate multiple distinct protein isoforms. It adds another regulation layer of gene expression. Up to 95% of human multi-exon genes undergo alternative splicing to encode proteins with different functions. Moreover, around 15% of human hereditary diseases and cancers are associated with alternative splicing. Regulation of alternative splicing is attributed to a set of delicate machineries interacting with each other in aid of important biological processes such as cell development and differentiation. Given the importance of alternative splicing events, their accurate mapping and quantification are paramount for downstream analysis, especially for associating disease with alternative splicing. However, deriving accurate isoform expression from high-throughput RNA-seq data remains a challenging task. In this mini-review, we aim to illustrate I) mechanisms and regulation of alternative splicing, II) alternative splicing associated human disease, III) computational tools for the quantification of isoforms and alternative splicing from RNA-seq.